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Boris Banushev
developerAI Quant and Data Scientist in Finance. Data Science MSc @ UC Berkeley. Economics PhD candidate @ Oxford. MSc Finance @ MBS. Yes, that's me
Public projects
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
JavaScript
anomaliesinoptions
In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
Jupyter Notebook
options-gpt
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Python
AIMLCICDonAWS
End to end CI/CD pipeline for AI/ML workloads built only using native AWS services.
Python
Likely stack
OpenAI
